The predictive value of laboratory parameters for no‐reflow phenomenon in patients with ST‐elevation myocardial infarction following primary percutaneous coronary intervention: A meta‐analysis

Abstract To date, the predictive role of laboratory indicators for the phenomenon of no flow is unclear. Hence, our objective was to conduct a meta‐analysis to investigate the association between laboratory parameters and the risk of the no‐reflow phenomenon in patients with ST‐elevation myocardial infarction (STEMI) following primary percutaneous coronary intervention (PCI). This, in turn, aims to offer valuable insights for early clinical prediction of no‐reflow. We searched Pubmed, Embase, and Cochrane Library from the establishment of the database to October 2023. We included case‐control or cohort study that patients with STEMI following primary PCI. We excluded repeated publication, research without full text, incomplete information or inability to conduct data extraction and animal experiments, reviews, and systematic reviews. STATA 15.1 was used to analyze the data. The pooled results indicated that elevated white blood cell (WBC) count (odds ratio [OR] = 1.061, 95% confidence interval [CI]: 1.013–1.112), neutrophil count (OR = 1.324, 95% CI: 1.128–1.553), platelet (PLT) (OR = 1.002, 95% CI: 1.000–1.005), blood glucose (OR = 1.005, 95% CI: 1.002–1.009), creatinine (OR = 1.290, 95% CI: 1.070–1.555), total cholesterol (TC) (OR = 1.022, 95% CI: 1.012–1.032), d‐dimer (OR = 1.002, 95% CI: 1.001–1.004), and fibrinogen (OR = 1.010, 95% CI: 1.005–1.015) were significantly associated with increased risk of no‐reflow. However, elevated hemoglobin was significantly associated with decreased risk of no‐reflow. In conclusion, our comprehensive analysis highlights the predictive potential of various parameters in assessing the risk of no‐reflow among STEMI patients undergoing PCI. Specifically, WBC count, neutrophil count, PLT, blood glucose, hemoglobin, creatinine, TC, d‐dimer, and fibrinogen emerged as significant predictors. This refined risk prediction may guide clinical decision‐making, allowing for more targeted and effective preventive measures to mitigate the occurrence of no‐reflow in this patient population.


| INTRODUCTION
3][4] Its widespread adoption over the past 12-15 years has been fueled by its remarkable clinical effectiveness. 5The merits of primary PCI were expounded by Rott, 6 while Goff et al. 7 demonstrated its superior efficacy, as compared to thrombolytic therapy, in restoring thrombolysis in myocardial infarction (TIMI) flow, consequently leading to a reduction in mortality.
Moreover, Singh 8 proposed that primary PCI is preferable to coronary artery bypass grafting (CABG), despite both procedures yielding similar outcomes in terms of quality of life.However, it is essential to note that favorable outcomes are not always guaranteed with primary PCI, as a commonly reported complication is the occurrence of the no-reflow phenomenon. 9,102][13] Diagnosis of the no-reflow phenomenon relies on several diagnostic methods, including angiography, myocardial contrast echocardiography (MCE), and cardiac magnetic resonance imaging (CMRI). 4MCE is considered the gold standard for diagnosing no-reflow, while CMRI is recognized as the most sensitive and specific approach for assessing the extent of no-reflow. 14According to various reports, the incidence of the no-reflow phenomenon varies, with rates ranging from 2% to 44% among patients undergoing both primary and elective primary PCI.The associated mortality with noreflow also exhibits variability, falling within the range of 7.4%-30.3%6][17] The pathogenesis of the noreflow phenomenon is intricate and dynamic, involving factors such as distal atherothrombotic embolization, ischemic injury, reperfusion injury, and an increased susceptibility of coronary microcirculation to damage. 18,19The pathogenesis of the no-reflow phenomenon is intricate and dynamic, involving factors such as distal atherothrombotic embolization, ischemic injury, reperfusion injury, and an increased susceptibility of coronary microcirculation to damage. 20Inflammatory mediators induce the expression of adhesion molecules on endothelial cells, promoting leukocyte adhesion and infiltration.This process can lead to microvascular plugging and compromise blood flow.Additionally, Inflammatory responses trigger endothelial cell activation, resulting in capillary endothelial swelling.The increased permeability may contribute to the obstruction of microvessels, exacerbating the no-reflow phenomenon 37498164.
The occurrence of the no-reflow phenomenon significantly elevates the risk of adverse clinical outcomes, including mortality, recurrent myocardial infarction (MI), decreased left ventricular ejection fraction (LVEF), left ventricular remodeling, malignant ventricular arrhythmias, heart failure (HF), and cardiac rupture.Given these detrimental effects, accurate detection of no-reflow, along with the identification of predictive factors, becomes of paramount importance.Currently, the predictive role of laboratory indicators for the no-reflow phenomenon remains unclear.Therefore, our objective was to conduct a meta-analysis to investigate the association between laboratory parameters and the risk of the no-reflow phenomenon in patients with STEMI following primary PCI.The ultimate goal is to provide valuable insights for the early clinical prediction of no-reflow.

| Literature inclusion and exclusion criteria
The inclusion criteria were as follows: the study design is a casecontrol or cohort study; patients with STEMI following PCI; studies reporting the risks of the no-reflow phenomenon; and the language is limited to English.
Exclusion criteria included studies that did not report relevant risk factors, studies focusing exclusively on elderly subjects, duplicate publications, research without full text, incomplete information, or an inability to conduct data extraction, animal experiments, and reviews and systematic reviews.

| Search strategy
In this meta-analysis, we searched Pubmed, Embase, Cochrane Library from establishment of the database to October 2023.The

| Literature screening and data extraction
The literature search, screening, and information extraction were all independently carried out by two researchers.In cases of uncertainty, decisions were reached through discussion or consultation with a third party.Data extraction encompassed author details, publication year, study design, country, sample size, no-reflow occurrence, demographic information such as sex and age, prevalence of hypertension and diabetes, number of smokers, and odds ratios (ORs) with corresponding 95% confidence intervals (95% CIs) for relevant risk factors.

| Literature quality assessment
Two researchers independently conducted quality assessments of the literature using the Newcastle-Ottawa Scale (NOS) 21 for cohort and case-control studies.In cases of discordant opinions, resolution was achieved through discussion or consultation with a third party.
The meta-analysis adhered to the relevant guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-analysis statement (PRISMA statement). 22

| Data synthesis and statistical analysis
Data analysis was conducted using STATA 15.1 (StataCorp LP) 23 was used to analyze the data.OR with 95% confidence intervals (95%CI) were utilized for analyzing the risk factors of cardiovascular and cerebrovascular disease subtypes.Heterogeneity was assessed using the I 2 statistic.If the heterogeneity test yielded a p ≥ .1 and I 2 ≤ 50%, indicating homogeneity among studies, the fixed-effects model was employed for combined analysis.In cases where p < .1 and I 2 > 50%, suggesting study heterogeneity, sensitivity analysis was performed (each trial was systematically excluded one by one, followed by a combined analysis of the remaining trials) to identify the source of heterogeneity.If substantial heterogeneity persisted, the randomeffects model was considered, or, if necessary, a descriptive analysis without combining results.As there were fewer than five articles for each indicator in the study, no publication bias detection was carried out.

| The results of literature search
In this study, a total of 484 studies were initially identified from the database.Following the removal of duplicate studies, 253 unique studies remained.After reviewing titles and abstracts, 49 publications were excluded, including 28 reviews and systematic reviews, 12 case reports, and 9 animal experiments.Consequently, a total of 204 studies met the inclusion criteria.Finally, 24 articles were included in the meta-analysis (Figure S1).

| Baseline characteristics and quality assessment of the included studies
A total of 20 case-control and four cohort studies were included in this meta-analysis, encompassing a cumulative sample size of 14,790 patients, among whom 2575 patients exhibited the noreflow phenomenon.Patients from 10 studies originated in China, while the remaining 14 studies involved patients from Turkey.Among all patients, the prevalence of hypertension ranged from 29.63% to 63.97%, diabetes ranged from 16.76% to 37.33%, and the history of smoking varied from 28.63% to 76.35%.The NOS scores used for quality assessment were consistently above 6 (Table 1).

White blood cell (WBC) count
Ten studies investigated the relationship between WBC count and the risk of no-reflow.Due to significant heterogeneity (I 2 = 73.6%,p = .000),a random-effects model was employed for the metaanalysis.The combined results revealed a significant association between an elevated WBC count and an increased risk of no-reflow (OR = 1.061, 95% CI: 1.013-1.112,p = .012;see Figure 1).

Neutrophil count
Four studies investigated the relationship between neutrophil count and the risk of no-reflow.Due to significant heterogeneity (I 2 = 85.7%, p = .000),a random-effects model was employed for the meta-analysis.
The combined results revealed a significant association between an elevated neutrophil count and an increased risk of no-reflow (OR = 1.324, 95% CI: 1.128-1.553,p = .001;see Figure 2).

Lymphocyte count
Four studies investigated the relationship between lymphocyte count and the risk of no-reflow.Due to significant heterogeneity (I 2 = 64.3%,p = .038),a random-effects model was employed for the meta-analysis.Pooled results show that there was no significant association between lymphocyte count and the risk of no-reflow (OR = 1.048, 95%CI: 0.827-1.328,p = .698;see Figure 3).

Neutrophil-to-lymphocyte ratio (NLR)
Three studies investigated the relationship between NLR and the risk of no-reflow.Due to significant heterogeneity (I 2 = 72.5%,p = .026),a random-effects model was employed for the meta-analysis.Pooled results show that there was no significant association between NLR and the risk of no-reflow (OR = 1.053, 95% CI: 0.957-1.158,p = .291;see Figure 4).

| Platelet (PLT)
Nine studies investigated the relationship between PLT and the risk of no-reflow.Due to significant heterogeneity (I 2 = 70.0%,p = .001),a random-effects model was employed for the meta-analysis.The combined results revealed a significant association between an elevated PLT and an increased risk of no-reflow (OR = 1.002, 95% CI: 1.000-1.005,p = .038;see

Figure S2).
T A B L E 1 Baseline characteristics and quality assessment of the included studies.Six studies investigated the relationship between blood glucose and the risk of no-reflow.Due to significant heterogeneity (I 2 = 71.4%,p = .004),a random-effects model was employed for the metaanalysis.The combined results revealed a significant association between an elevated plasma glucose and an increased risk of noreflow (OR = 1.005, 95% CI: 1.002-1.009,p = .004;see Figure S3).

| Hemoglobin
Twelve studies investigated the relationship between hemoglobin and the risk of no-reflow.Due to significant heterogeneity (I 2 = 97.5%,p = .000),a random-effects model was employed for the meta-analysis.The combined results revealed a significant association between an elevated hemoglobin and a decreased risk of noreflow (OR = 0.885, 95% CI: 1.002-1.009,p = .000;see Figure S4).

| Renal function index
Estimated GFR (eGFR) Four studies explored the association between eGFR and the risk of no-reflow.As there was no significant heterogeneity (I 2 = 45.1%,p = .141),a fixed-effects model was used for the meta-analysis.The combined results indicated no significant association between eGFR and the risk of no-reflow (OR = 0.994, 95% CI: 0.986-1.001,p = .108;see Figure S5).

Creatinine
Five studies investigated the relationship between creatinine and the risk of no-reflow.Due to significant heterogeneity (I 2 = 88.4%,p = .000),a random-effects model was employed for the meta-analysis.The combined results revealed a significant association between an elevated creatinine and an increased risk of no-reflow (OR = 1.290, 95%CI: 1.070-1.555,p = .008;see Figure S6).
F I G U R E 1 Association of white blood cell count and the risk of no-reflow.CI, confidence interval; OR, odds ratio.

| Lipid index
Total cholesterol (TC) Four studies investigated the relationship between TC and the risk of no-reflow.As there was no significant heterogeneity (I 2 = 0.0%, p = .958),a fixed-effects model was used for the meta-analysis.
The combined results revealed a significant association between an elevated TC and an increased risk of no-reflow (OR = 1.022, 95%CI: 1.012-1.032,p = .000;see Figure S7).

TG
Ten studies explored the association between TG and the risk of noreflow.Due to significant heterogeneity (I 2 = 45.0%,p = .060),a randomeffects model was employed for the meta-analysis.The combined results indicated no significant association between TG and the risk of no-reflow (OR = 1.000, 95% CI: 0.997-1.004,p = .844;see Figure S8).

D-dimer
Four studies investigated the relationship between D-dimer and the risk of no-reflow.As there was no significant heterogeneity (I 2 = 40.4%,p = .169),a fixed-effects model was used for the metaanalysis.The combined results revealed a significant association between an elevated D-dimer and an increased risk of no-reflow (OR = 1.002, 95% CI: 1.001-1.004,p = .008;see Figure S9).

Fibrinogen
Three studies investigated the relationship between fibrinogen and the risk of no-reflow.As there was no significant heterogeneity (I 2 = 0.0%, p = .953),a fixed-effects model was used for the meta-analysis.The combined results revealed a significant association between an elevated fibrinogen and an increased risk of no-reflow (OR = 1.010, 95% CI: 1.005-1.015,p = .008;see Figure S10).

| hsCRP
Five studies explored the association between hsCRP and the risk of no-reflow.Due to significant heterogeneity (I 2 = 88.5%,p = .000),a random-effects model was employed for the meta-analysis.The combined results indicated no significant association between hsCRP and the risk of no-reflow (OR = 1.052, 95% CI: 0.990-1.118,p = .105;see Figure S11).
F I G U R E 2 Association of white blood cell count and the risk of no-reflow.CI, confidence interval; OR, odds ratio.

| Sensitivity analysis
By doing a meta-analysis, we found that all the meta-analyses did not have much effect on the results of the meta-analysis, indicating that the results of the meta-analysis were stable and reliable.

| Publication bias
The funnel plot depicted in this study is presented below, revealing a predominantly symmetrical distribution.The obtained p value from Egger's test was .139,suggesting the absence of significant publication bias in this study (Figure S12).

| CONCLUSION
In conclusion, our comprehensive analysis highlights the predictive potential of various parameters in the risk of no-reflow among STEMI patients undergoing PCI.Specifically, WBC count, neutrophil count, PLT, blood glucose, hemoglobin, creatinine, TC, D-dimer, and fibrinogen emerged as significant predictors.These findings present valuable insights for clinicians, suggesting that incorporating these biomarkers into risk assessment protocols can enhance the identification of individuals at higher risk of experiencing no-reflow post-PCI in STEMI cases.This refined risk prediction may guide clinical decision-making, allowing for more targeted and effective preventive measures to mitigate the occurrence of noreflow in this patient population.

| DISCUSSION
The pathogenesis of no-reflow and its associated risk factors are not fully understood.However, existing literature suggests several mechanisms that may contribute to this phenomenon, including (1)   pre-existing microvascular dysfunction; (2) distal microthromboembolization caused by elevated platelet activity and a significant thrombus burden; (3) ischemic injury; (4) reperfusion injury; (5)   swelling of myocardial cells, resulting in the compression of microvascular vessels; and (6) individual susceptibility. 20,48,49While some studies have reported potential risk factors including advanced age, male, family history of coronary artery disease, smoking, diabetes mellitus, hypertension, and delayed reperfusion, these reports have been accompanied by inconsistencies.Furthermore, the relationship between laboratory parameters and the no-reflow phenomenon remains uncertain.This study, for the first time, conducted a meta-analysis to investigate the predictive role of  50 This outcome provides further support for the objectivity of our analysis.Additionally, the combined results indicated a significant association between an elevated platelet count (PLT) and an increased risk of no-reflow (OR = 1.002).However, the OR value was only 1.002, suggesting that platelet changes may not be a crucial factor in the occurrence of no-reflow.
In addition to blood indices, we also examined the association of blood glucose and hemoglobin with the risk of no-reflow.The aggregated results revealed a significant association between elevated blood glucose levels and an increased risk of no-reflow, with an OR value of 1.005.Conversely, elevated hemoglobin levels were significantly associated with a lower risk of no-reflow.This suggests that hemoglobin acts as a protective factor against the noreflow phenomenon, and the occurrence of no-reflow can potentially be prevented by supplementing hemoglobin in clinical treatment.It is noteworthy that hemoglobin-based oxygen carriers, such as Stromafree hemoglobin nanoparticles, have demonstrated neuroprotective effects in ischemia-reperfusion injury. 51reover, elevated creatinine levels were identified as being associated with an increased risk of no-reflow.This implies that individuals with STEMI and impaired renal function should exercise particular caution to prevent no-reflow after PCI.Additionally, increased levels of TC, D-dimer, and fibrinogen were also significantly associated with an elevated risk of no-reflow.This suggests that lipid F I G U R E 4 Association of neutrophil-to-lymphocyte ratio and the risk of no-reflow.CI, confidence interval; OR, odds ratio.
accumulation and sluggish blood flow may contribute to the occurrence of no-reflow.
This meta-analysis has several limitations.Firstly, heterogeneity was observed in the studies of some indicators, and while sensitivity analysis revealed no studies significantly influencing the results, the source of heterogeneity may be attributed to variations in the correction of results.This study extracted OR values from regression analysis sources for summary, but only a subset of studies corrected their results.Secondly, the included literature was obtained through electronic searches and comprised solely of published studies.
Unpublished literature was not taken into consideration.Third, other hemogram parameters-based markers (e.g., PLR, SII, PIV) did not meet the criteria for inclusion in the meta-analysis for the studies included in this research.Therefore, analysis of these markers was not feasible in the current study.Future investigations will necessitate the inclusion of additional studies to facilitate the analysis of hemogram parameters-based markers beyond NLR.

F I G U R E 3
Association of lymphocyte count and the risk of no-reflow.CI, confidence interval; OR, odds ratio.laboratory parameters in the occurrence of the no-reflow phenomenon, with the aim of offering guidance for clinical treatment.Initially, the combined results indicated a noteworthy association between an elevated WBC count and an increased risk of no-reflow (OR = 1.061).Particularly significant was the observation that an increased neutrophil count, a specific type of leukocyte, demonstrated a stronger association with an increased risk of no-reflow (OR = 1.324 > 1.061).These findings suggest that the connection between WBC and the risk of no-reflow is predominantly influenced by neutrophils.The findings confirm the involvement of microvascular inflammation in the pathogenesis of no-reflow.This discovery provides concrete guidance for clinicians, enabling them to more accurately assess patients' risk of no-reflow and implement targeted interventions.By incorporating neutrophil count into risk assessment and diagnostic criteria, clinicians can identify patients more precisely and offer personalized and precise treatment plans.This understanding also underscores the importance of inflammation in treatment strategies, opening new directions for future research and therapies.Overall, these findings offer substantial clinical guidance for improving the management of cardiovascular disease patients.Interestingly, a study conducted by Gullotta et al. in vivo demonstrated that in an experimental stroke, older mice exhibited greater neutrophil blockage in the microcirculation of the ischemic brain compared to younger mice, leading to more severe no-reflow and poorer outcomes.